Disentangling viral respiratory infections and coinfection: a modelling approach that links population surveillance and experimental data
Lead Research Organisation:
University of Glasgow
Department Name: College of Medical, Veterinary, Life Sci
Abstract
Studentship strategic priority area:Population Health Sciences and Public Health
Keywords: Respiratory viruses, modelling, virus-virus interactions, quantitative analysis
Multiple viruses are responsible for respiratory infections and co-infections that causing a range of disease, from a mild cold to life-threatening pneumonia. Respiratory viruses are generally studied as single entities and not as a community. However, evidence suggest that there are interactions between viruses that are important for patient health and for infection dynamics at the population scale. Mathematical models are essential tools for the control of infectious diseases and have been used extensively at the population scale. However, only a handful of studies have focused on the individual host scale and even less attention has been paid to coinfections. This project will use data from experimental infections and coinfections to model virus-virus interactions. We will combine quantitative data on virus entry, virus replication, virus spread, innate immune kinetics and cellular death and regeneration. Results from this work will identify the relative roles of direct (virus-virus) and indirect (virus-immune response) interactions in coinfections with the goal of improving patient care.
Keywords: Respiratory viruses, modelling, virus-virus interactions, quantitative analysis
Multiple viruses are responsible for respiratory infections and co-infections that causing a range of disease, from a mild cold to life-threatening pneumonia. Respiratory viruses are generally studied as single entities and not as a community. However, evidence suggest that there are interactions between viruses that are important for patient health and for infection dynamics at the population scale. Mathematical models are essential tools for the control of infectious diseases and have been used extensively at the population scale. However, only a handful of studies have focused on the individual host scale and even less attention has been paid to coinfections. This project will use data from experimental infections and coinfections to model virus-virus interactions. We will combine quantitative data on virus entry, virus replication, virus spread, innate immune kinetics and cellular death and regeneration. Results from this work will identify the relative roles of direct (virus-virus) and indirect (virus-immune response) interactions in coinfections with the goal of improving patient care.
Organisations
People |
ORCID iD |
Louise Matthews (Primary Supervisor) | |
Dorottya Kovacs (Student) |
Studentship Projects
Project Reference | Relationship | Related To | Start | End | Student Name |
---|---|---|---|---|---|
MR/S502479/1 | 01/10/2018 | 31/07/2022 | |||
2127249 | Studentship | MR/S502479/1 | 01/10/2018 | 31/03/2022 | Dorottya Kovacs |